Hi Jacopo, it’s definitely worth it. I found 3DVA was very informative in deciding where to place a mask for 3D classification without alignments, but cryoSPARC just can’t seem to give good particle sets based on the movements (I may be doing something wrong). 3D classification can find very small movements and give nice discrete particle stacks for further refinement. In my experience, heterogeneous refinement in cryoSPARC is useful to remove bad particles to increase resolution of a final stack or to separate moderately dissimilar states. Yet it seems to latch onto very stable core of the protein and masks out regions with movement, which is often where the action is.
I’ve been getting best (& fast) results using a tight box around my particle with binning to 1.25A. It usually takes a few iterations to get a feel for the right settings, so getting it to go fast helps a lot. I’ll test T parameter at 80, 200, or 400 (without alignments), into 8 or up to 20 classes. I like to extract in cryosparc with fourier crop, ab initio, refine, csparc2star, import it all to relion + custom mask (or start with csparc refine mask) and spend a few days (or weeks) running 3D classification. It reveals things that cryosparc just cannot find (yet). See another endorsement here.
If you need any help with pyem, feel free to shoot me a DM and I’ll do my best to help.